The Bag-of-Words (BoW) representation is one of the most widely used method for image retrieval [1]}, [2]}. It quantizes each local descriptor SIFT [3]} or SURF [4]}, to its nearest cluster center and encodes each image as a histogram over cluster centers also known as “Visual Words”. Good retrieval performance is achieved with a high dimensional sparse BOW vector, in which case inverted lists can be used to implement efficient search. However, the search time grows quadratically as the number of images increase [5]}.
